paper
2018
Observations & remote sensing
Post-processing & calibration New model or method
Classical ML (trees, GP, linear, kernels)University of Washington Journal
2018-01-04
026
Jan 2018
Callie McNicholas, Clifford F. Mass
Journal of Atmospheric and Oceanic Technology
University of Washington
Machine learning corrects smartphone barometer biases using ancillary sensor data, cutting average pressure bias by 82% and supporting use in NWP.
Smartphone Pressure Collection and Bias Correction Using Machine Learning
In one sentence. Machine learning corrects smartphone barometer biases using ancillary sensor data, cutting average pressure bias by 82% and supporting use in NWP.
Labels
- Topic
- Observations & remote sensing, Post-processing & calibration
- Type
- New model or method
- Method
- Classical ML (trees, GP, linear, kernels)
- Domain
- Global
- Data
- Station / in-situ, Other
- Status
- Research
- Identifiers
- DOI:10.1175/jtech-d-17-0096.1 OpenAlex:W2782459188
- Added
- 2026-10-22
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